A Network Security Situational Awareness Model Based on Information Fusion

2013 ◽  
Vol 846-847 ◽  
pp. 1632-1635
Author(s):  
Abasi
Keyword(s):  
Network Security ◽  
Information Fusion ◽  
Situational Awareness ◽  
Evidence Theory ◽  
Arma Model ◽  
Situational Factors ◽  
Source Information ◽  
Network Nodes ◽  
Model Based ◽  
The Future

Security situational awareness has become a hot topic in the area of network securityresearch in recent years. The existing security situational awareness methods are analyzed and compared in details, and thus a newnetwork security situational awareness model based on information fusion is proposed. This modelfuses multi-source information from a mass of logs by introducing the modified D-S evidence theory,gets the values of nodes security situational awareness by situational factors fusion using attacks threat,and vulnerability information which network nodes have and successful attacks depend on, computesthe value of network security situational awareness by nodes situation fusion using service informationof the network nodes, and draws the security-situation-graph of network. Then, it analyzes the timeseries of the computing results by ARMA model to forecast the future threat in network security.Finally an example of actual network datasets is given to validate the network security situationalawareness model and algorithm. The results show that this model and algorithm is more effective andaccurate than the existing security situational awareness methods.

Network Security Situation Awareness Based on Multi-Source Data Fusion

2014 ◽  
Vol 989-994 ◽  
pp. 4885-4888 ◽  
Author(s):  
Gang Chen ◽  
Jun Ping Cai ◽  
Jun Yang
Keyword(s):  
Network Security ◽  
Situation Awareness ◽  
Situational Awareness ◽  
Evidence Theory ◽  
System Level ◽  
Source Information ◽  
Security Research ◽  
Data Source ◽  
Source Level ◽  
Level Fusion

Network security situation awareness is an effective way to analysis security situation of complex network.The concept and model of network security situational awareness was introduced.A new model of network security situation awareness was proposed. Considering the characteristics of multi-source information in network security research, a security situation awareness algorithm based on information fusion was adopted. This algorithm advanced modified D-S evidence theory, gets the values of security situation awareness of network by data source level fusion, host-level fusion and system-level fusion. The results can reflect the general security state of network.

scholarly journals Research on the Key Technologies of Network Security-Oriented Situation Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yikun Zhu ◽  
Zhiling Du
Keyword(s):  
Network Security ◽  
Situational Awareness ◽  
Algorithm Design ◽  
Evidence Theory ◽  
Assessment Model ◽  
Time Varying ◽  
Security Threat ◽  
Model Based ◽  
Posture Assessment ◽  
Threat Posture

In today’s increasingly severe network security situation, network security situational awareness provides a more comprehensive and feasible new idea for the inadequacy of various single solutions and is currently a research hotspot in the field of network security. At present, there are still gaps or room for improvement in network security situational awareness in terms of model scheme improvement, comprehensive and integrated consideration, algorithm design optimization, etc. A lot of scientific research investments and results are still needed to improve the form of network security in a long and solid way. In this paper, we propose a network security posture assessment model based on time-varying evidence theory for the existing multisource information fusion technology that lacks consideration of the problem of threat occurrence support rate over time and make the threat information reflect the law of time change by introducing a time parameter in the basic probability assignment value. Thus, the existing hierarchical threat posture quantitative assessment technique is improved and a hierarchical multisource network security threat posture assessment model based on time-varying evidence theory is proposed. Finally, the superiority of the proposed model is verified through experiments.

An Extraction Method of Situational Factors for Network Security Situational Awareness

2008 ◽  
Author(s):  
Huiqiang Wang ◽  
Ying Liang ◽  
Haizhi Ye
Keyword(s):  
Network Security ◽  
Extraction Method ◽  
Situational Awareness ◽  
Situational Factors

Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

2013 ◽  
Vol 791-793 ◽  
pp. 1018-1022
Author(s):  
Peng Wang ◽  
Zhi Qiang Liu
Keyword(s):  
Information Fusion ◽  
Evaluation System ◽  
Evidence Theory ◽  
Recognition System ◽  
Fusion Method ◽  
Source Information ◽  
State Recognition ◽  
Research On Evaluation ◽  
Lane Departure ◽  
Level Information

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

Software Development and Design of Network Security System Under Big Data Analysis

2020 ◽  
pp. 135-140
Author(s):  
Mei Hong Chen
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Network Security ◽  
Radial Basis Function ◽  
Basis Function ◽  
Situational Awareness ◽  
Cuckoo Search ◽  
Function Model ◽  
Model Based ◽  
Radial Basis

To explore the prediction effect of network security situational awareness on network vulnerabilities and attacks under the background of big data, this study constructs a predictive index system based on the network security situational awareness model. Based on the improved cuckoo algorithm, the cuckoo search radial basis function neural network is used to predict the situation. The weight value in the model is determined by the hierarchical analysis method, vulnerability simulation is conducted by Nessus software and network attack simulation is conducted by Snort software, and then the situation is evaluated by a fuzzy comprehensive evaluation method. Finally, Jquery and Bootstrap software is used to develop the system. The results show that the cuckoo search radial basis function model proposed in this study could predict network security situations more accurately than the radial basis function model, cuckoo search back-propagation neural network model, genetic algorithm radial basis function model and Support vector machine model based on particle swarm optimization model.

scholarly journals Innovative assessment scheme of navigation risk based on improved multi-source information fusion techniques

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877254
Author(s):  
Bo Li ◽  
Fuwen Pang
Keyword(s):  
Information Fusion ◽  
Time Complexity ◽  
Euclidean Distance ◽  
Evidence Theory ◽  
Classification Model ◽  
Support Vector ◽  
Source Information ◽  
Distance Ratio ◽  
Slack Variable ◽  
Nonlinear Support

To deal with highly time complexity and unstable assessments for conflicting evidences from various navigation factors, we put forward an innovative assessment scheme of navigation risk based on the improved multi-source information fusion techniques. Different from the existing studies, we first deduce the nonlinear support vector machine classification model for the general scenario. The slack variable is adaptively computed based on the Euclidean distance ratio. Considering the unsatisfactory characteristics of the standard Dempster–Shafer evidence theory, the optimal combination rule is derived step by step. What"s more, the lowly dimensional Kalman filter is applied to forecast the navigation risk. Simultaneously, the time complexity of each technique is analyzed. With respect to the vessel navigation risk, the assessment results are provided to indicate the reliability and efficiency of the proposed scheme.

Research Based on Information Fusion of Safety Risks Prediction and Control Management in Construction

2011 ◽  
Vol 480-481 ◽  
pp. 1502-1506
Author(s):  
Ping Zhao ◽  
Hu Zhang
Keyword(s):  
Information Fusion ◽  
Construction Projects ◽  
Evidence Theory ◽  
Construction Safety ◽  
Source Information ◽  
Accident Rate ◽  
Safety Risks ◽  
Prediction And Control ◽  
Hazard Sources ◽  
And Control

Safety risks management of safety potential information and hazard sources has been taken in Construction process. It is the most important measure to solve the current situation that safety accidents is frequent in Chinese Construction projects. The main reasons of frequent accidents were find out and the D-S evidence theory of multi-source information fusion method was used to reduce the accident rate in Construction safety in this paper. Through analyzing and predicting the engineering data and information in human, machine, environment and management four aspects in Construction, prediction model was built in Construction safety risks management, the possibility of dangerous and harmful level in the construction project can be known, preventive measures for specific situations were taken and promptly the safety state of the Construction will be ensured.

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